Caps project

Seeherunwong et al. International Journal of Mental Health Systems (2022) 16:3 https://doi.org/10.1186/s13033-022-00514-1

R E S E A R C H

Staffing and patient-related factors affecting inpatient falls in a psychiatric hospital: a 5-year retrospective matched case–control study Acharaporn Seeherunwong1* , Chanya Thunyadee1, Wipa Vanishakije2 and Pavinee Thanabodee‑tummajaree2

Abstract Background: The frequency and severity of falls of psychiatric inpatients in Thailand have not been previously reported. Also, the risk factors of falls have been numerous and complicated. This study aimed to investigate the staff‑ ing factors and patient‑related factors that increase the likelihood of falls among psychiatric inpatients.

Methods: A five‑year retrospective matched case–control study was conducted that selected cases of inpatients who fell and which were reported to the hospital risk management system. Subjects were compared to two control patients from the same hospital (1:2) by age (± 5 years), sex, and admission the same year. The total sample consisted of 240 patients. Univariate and multivariate conditional logistic regression was used to analyze the data.

Results: Of the eighty falls, 86.3% resulted in temporary harm and required intervention. The multivariate model showed that three patient‑related factors were associated with increased inpatient falls: (1) having an acute psychotic condition (adjusted odds ratio (AOR) = 4.34; 95% CI 1.45, 13.05; p < 0.05), (2) polypharmacy with more than four types of medicines (AOR = 3.06; 95% CI 1.59, 5.88; p < 0.05), and (3) taking atypical psychiatric drugs (AOR = 2.74; 95% CI 1.35, 5.58; p < 0.05). Staffing for 26–50 patients in the wards was more protective for falls than with 25 or fewer patients (AOR = .17; 95% CI 0.04, 0.72; p < 0.05). Conclusions: The risk factors found may help assess fall risk and manage the number of patients in psychiatric units. Drug dosage and drug interaction of antipsychotic drugs and cardiovascular agents with other medications and drug administration timing before falls are recommended for further investigation. Also, staff ratio per patient and the proportion of staff mix in psychiatric units need further study to establish adequate levels of surveillance to prevent inpatient falls.

Keywords: Accidental falls, Case–control studies, Psychiatric hospitals, Risk factors, Staffing

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Introduction Inpatient falls are an indicator representing quality of care and preventable patient safety issues. Incidence in psy- chiatric units is 3–4 times falls in general medical units [1]. Compared with nursing home and medical-surgical

units, inpatient falls in psychiatry settings have a higher incidence and greater severity [2]. Among all inpatient falls, physical injury is reported thirty percent of the time [3], with four percent serious injury [4].

Falls are a significant cause of morbidity and mor- tality among psychiatric patients. Falls affect recovery from illness, increase the length of hospital stay, and increase healthcare costs. Moreover, the additional cost of lawsuits from injured patients’ families against hospi- tal administrators is significant [3]. In particular, in fall- related severe injuries, the results are loss of function,

Open Access

International Journal of Mental Health Systems

*Correspondence: [email protected] 1 Department of Mental Health and Psychiatric Nursing, Faculty of Nursing, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Patthom 73170, Thailand Full list of author information is available at the end of the article

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loss of life, and financial burden [5]. Operational costs for those who fall with serious injury are $ 13,316 more than without a fall, and the length of hospital stay is longer by up to 6.3  days [6]. The psychological impact of falling is fear of a repeated fall, causing patients to restrict their activities.

Factors increasing the risk of falls in a psychiatric set- ting are complex. The individual level and the organi- zation level or system level affect the fall incidence for psychiatric inpatients. Also, Currie [7] classified the risk factors of falls as intrinsic or extrinsic factors. Intrinsic factors have a physiological origin, while extrinsic fac- tors are those that result from environmental or other hazards. Previous studies identified various conditions as intrinsic factors contributing to psychiatric inpatient falls. A 5-year case–control study reported more physical complaints on the day of the fall, and the prescription of Clonazepam was the most significant predictor of falling [8]. The physical complaints of urinary frequency, gen- eralized weakness, mental status impairment, and dizzi- ness were more frequent among those who fell. Also, the presence of an acute medical condition, more medica- tion, and being prescribed anti-hypertensive medication were differences between those who did or did not fall. Depressed patients aged 20 years and under had a lower risk (relative risk 0.45), and patients between 60 and 70 years old with psychosis had a higher risk (relative risk 2.86) than patients in their respective age groups without these diagnoses [9].

Although psychotropic medications are essential for treating patient symptoms, controversially, such medi- cations were the strongest predictor of falls. A study of psychiatric, geriatric inpatients ≥ 70  years of age taking typical antipsychotic or antidepressants had higher fall incidents [10]. Liperoti et  al. [11] also found that elderly institutionalized patients using both atypical and typical antipsychotics had an increased risk of hospitalization for femur fracture than non-users. A prospective matched case–control study [12] reported three out of four factors relating medicine to increased risk of falling. The risk was associated with Parkinson’s scores on the extrapyramidal syndrome rating scale, the equivalent dosage of benzo- diazepines used, and medication changes within 24  h. These significant factors were associated with falls, a his- tory of falls in the past 6 months, and a lack of history of medical problems.

Most previous studies have shown that patient factors associated with increased falls in psychiatric units are intrinsic factors. Also, the assessment tools and strategies to prevent falls come from intrinsic or patient factors. However, many studies have addressed the importance of system-level or organization-level on reducing fall incidences in psychiatric units. Notably, nursing staff ’s

perception of patient safety in psychiatric inpatient care brings attention to the care environment’s crucial role and adequate staffing resources [13, 14].

As Thailand is an upper-middle-income country, health resources are limited in many aspects such as medicine, equipment, financial and staffing. Regarding inpatient falls, time spent providing attention from health workers is crucial; the number of patients per health staff is asso- ciated with patients’ safety [15]. Evidence of a systematic review has shown that higher nurse-patient ratios are associated with decreased inpatient mortality [16]. In inpatient falls, the association between staffing in terms of the number of register nurse (RN) hours and mixed staff hours was unequivocal. A few exceptional recent studies report an association between RN staffing and the rate of dangerous falls varies by unit type [17]. For exam- ple, Lake, Shang, Klaus, Dunton [18] showed a negative association between RN staffing levels and fall rates in intensive care units (ICUs).

Conversely, the level of non-nurse staffing, both Licensed Practical Nurses and assistant nurses, showed a positive association with fall rates in non-ICUs. As in psychiatric units, evidence about staffing factors and fall rates is rare. This current study considers mental health service delivery system in term of human resources including nursing staff and unlicensed nurse assistants in the team to patient ratio and proportion of skill mix to be an extrinsic factor related to falls. Intrinsic factors are included in this current study as well. This study aims to explore fall characteristics and investigate the patient- related and staffing factors that increase the likelihood of falls among psychiatric inpatients. Our results may lead to a better understanding of the multiple factors affecting inpatient falls, and it provides evidence for policy deci- sions on patient safety care in psychiatric hospitals.

Methods A retrospective matched case–control study of psychi- atric inpatients matched one patient who had fallen with two control patients who had not by age, sex, and admis- sion year. The study was conducted at a psychiatric hos- pital located in Bangkok, Thailand.

Definitions In this study, falls were defined as an event resulting in a person coming to rest inadvertently on the ground or floor or other lower level. Falls may be fatal or non- fatal and exclude those due to assault and self-harm, though most are non-fatal [19]. Intentional falls in which a patient intentionally descends to the floor were also excluded [20]. Incidents of falls reported to the hospital risk management system were considered cases of falls in this study. The impact of falls was also categorized into

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five levels of harm (Level E to I), based on the National Coordinating Council for Medication Error Reporting and Prevention classification system [21]. The descrip- tion of each level is: Level E = resulted in temporary harm to the patient and required intervention, F = resulted in temporary harm to the patient and required initial or prolonged hospitalization, G = resulted in permanent patient harm, H = required intervention necessary to sustain life, and I = resulted in the patient’s death. How- ever, in this study, the levels of harm was obtained ranged from level E to Level G.

Sample size The sample size was determined using Stata 17.0 to test of association in a 1:2 matched case–control study using conditional logistic regression at a 5% significance level (α), to yield a statistical power (1-β) of 80%. In a previ- ous study, fall incidence in a state psychiatric hospital 0.041 [22] and the odds ratio of exposure to Clonazepam (a benzodiazepine medication) in cases relative to con- trol = 4.05 [8]. Seventy-four cases of falls and 148-con- trols were required. Assuming 80% of staff reported complete information for both patients and controls, 89 potential cases were sought. According to the 5-year case reports of fall incidences of the hospital, there were 120 cases. However, researchers could find complete information for only 80 patients, accounting for 66.66% of total cases. Therefore, 80 cases of inpatients who fell and 160 inpatients who never fell were included in the analysis.

Setting The study was conducted at a psychiatric hospital, gov- erned by the Department of Mental Health, Ministry of Public Health. The hospital is located in Bangkok and was established in 1889. The hospital is a training insti- tute in mental health, psychiatry, and neuropsychiatry for health professionals. The inpatient service has 800 beds, divided into four 15- to 20-bedded private wards, four 60- to 80-bedded ordinary wards, and two 50- to 60-bed- ded wards for elderly patients. Also, the hospital has a 12 bed-pre ICU ward. The pre-ICU ward was established in 2012 for patients who expressed severe violence toward themselves and others. Hospitals developed criteria to prevent falls by classifying risk into three levels: severe, moderate, and mild. The fall risk levels are evaluated at the day of admission and later by items including (1) his- tory of falling within 1 month, (2) history of any of five ill- nesses: epilepsy, hypertension, diabetes, cerebrovascular accident (CVA), or osteoarthritis, (3) impaired self-help abilities or disability, (4) a condition of imbalance, such as lack of nutrient or electrolyte imbalance, (5) age 60 years or over, (6) behavior of rapid movement and lack of

caution, (7) use of 3 or more drug combined at the same time, (8) use of the drugs chlorpromazine, clonazepam, or clozapine. Each risk level’s recommended action was as follows: The group at risk of serious fall was assigned 1:1 staff care with limited behavior as needed and pro- vided supportive devices. Moderately and mild vulner- able fall groups were assigned in-sight, close care staff.

Data Cases were defined as psychiatric inpatients aged 18  years or older, having a documented fall reported to the hospital’s risk management center between January 1st, 2011 and December 31st, 2014. If a patient fell more than once during admission or another admission in the data collection period, only the first fall on admission was used. Cases were matched to two control patients from the same hospital (1:2) by age (± 5 years), sex, and admis- sion year. The reason for dual controls per case was the rarity of reported cases of falls in the hospital. Each con- trol patient was recruited by purposive sampling based on the match-criteria.

Data on characteristics of falls were obtained from the hospital incident reports for the risk management sys- tem. The fall incidents data included year, day of the week (Monday to Sunday), time of the day, type of the ward (specialized, ordinary, and pre-ICU), and level of injury impact. Demographic and clinical data (patient-related factors), were collected from case and control subjects from the patients’ history folders. Staffing-related data were obtained from nursing administrator records of the hospital. All data were extracted and recorded by a trained nursing staff member who has worked for 20 years at the hospital. The record form for data collec- tion has three parts. Part 1 is demographic data, com- prised of sex, age, marital status, education level, history of falls, consciousness before the fall occurred, and injury level from the fall. Part 2 included clinical data consist- ing of psychiatric and other diagnoses, all medications received within the previous 24  h, the number of drugs prescribed, and the duration from admission to the fall occurring. Part 3 documented staffing data and com- prised the number of nurses and unlicensed nurse assis- tants (ULNs) on duty, number of patients in the shift, and duration of on-duty hours, both for nurses and ULNs.

The nurse-to-patient ratio was calculated as a staff- related factor by dividing the total number of patients on the ward by the total number of registered nurses during the shift. For analysis, we categorized the nurse- to-patient ratio into three levels: one nurse per 1–15 patients, one nurse per 16–30 patients, and one nurse per 31–45 patients. A score for mixed skills was calcu- lated by summing the working hours of all nurses on the shift divided by the summed total of the working hours

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of ULNs on the shift. In this study, proportions of mixed skills were calculated to be four values: 0.33, 0.50, 0.67, or 1.00. The number of patients staying in the unit was categorized into three groups: equal or lower than 25, 26–50, and more than 50 patients. The number of nurses and number of ULNs on duty was categorized into two groups: at least one staff member working on the shift, one nurse and above, two ULNs and above, respectively.

Ethics This study was reviewed and approved by the Faculty of Nursing Institutional Review Board (COA No. IRB-NS 2015/282.3004) and Review Board committees of the psychiatric hospital. The data history of fall cases and the control group were accessed and recorded in the data collecting form by hospital staff trained to collect data from inpatient folders.

Statistical analyses Descriptive statistics were reported for fall incident char- acteristics and demographic data of the case and con- trol group. Since the fall cases and those who did not fall were match pairs (1:2), comparisons between falls and controls, categorical variables were tested by McNemar test, continuous variables with normal distribution were tested by paired t-test. We used univariate and multi- variate conditional (fixed-effects) logistic regression with 95% confidence intervals (CI) to evaluate the association of patient-related factors and staff factors with the risk of fall, displayed as odds ratios. Regarding univariate conditional logistic regression analysis, any significant variable (p ≤ 0.15) related to fall was considered for their possible inclusion in the multivariate logistic regression model. A previous study supported a cut-off value of 0.15 for potential variables contributing to the final model [23]. The final multivariate logistic regression model was selected after assessing the multivariate models’ ade- quacy by Akaike’s information criteria (AIC) and Hos- mer–Lemeshow goodness-of-fit test. The model with the lowest AIC value compared to other models was selected. Potential interaction between covariates in the model were checked before use in the final model. A p < 0.05 was considered statistically significant. All p values were two- tailed. The statistical software used for all analyses was Stata17.0

Results Of the 80 patients who had fallen and the 160 who had not, 67.5% were male in both groups. The mean age of those who had fallen was 47.37 years, ± SD = 12.95 (range 20–70), and was 47.01 years, ± SD = 13.19 (range 18–70) for controls. The number of patients whose marital status was single, separated, or divorced was 2–3 times greater

than those who lived as a couple in both groups. Patients who had had primary school education (6  years) were fewer in number than those who had graduated from secondary school or higher in both groups. Nine patients had fallen in the past 6  months with no such experience among controls. Both groups had frequent diagnoses of schizophrenia, followed by those with bipolar disorder. Comparisons of demographic data for inpatients who fell and controls are shown in Table 1.

Fall incident characteristics The majority of fall incidents were reported in 2014 (27.8%). The day with the highest frequency of falls was Tuesday. Fall incidents occurred more frequently in the ordinary ward than in the special ward and pre-ICU ward. Times of having falls indicate the highest frequency is during the night shift (midnight.  - 8.00 am.) (57.5%). Some 55.4% of the patients fell after 2 weeks of hospitali- zation, and 30.1% fell within the first seven days of hos- pitalization. Locations of the falls were most likely the bedroom (43.8%) and the bathroom (37.5%). Activities during falls were bathroom-related (42.5%) and getting up from the bed or chair (30%), respectively. The charac- teristics of incidents of falls are shown in Table 2.

Univariate analysis of risk factors for inpatient falls Univariate analysis revealed that inpatients who fall were significantly more likely to have acute psychosis (uOR = 6.88, 95% CI 2.56, 18.53), have a co-occurring physical illness, and use drugs with five or more types of medicines (uOR = 2.97, 95% CI 1.57, 5.63; uOR = 3.91, 95% CI 2.10, 7.29). Univariate analysis also showed that taking an atypical antipsychotic medication or cardio- vascular agent significantly increased the risk of a fall (uOR = 2.64, 95% CI 1.48, 4.70; uOR = 2.17, 95% CI 1.05, 4.51 respectively). In contrast, taking a typical psychiatric drug significantly reduced the risk of a fall (uOR = 0.53, 95% CI 0.31, 0.92). Staffing factors that could substantially protect the risk of a fall included the nurse-to-patient ratio and the number of patients in the ward. The results showed that one nurse for 16–30 patients and one nurse for 31–45 patients compared to one nurse for 15 patients decreased risk of fall by 0.28 and 0.17 times respectively (95% CI 0.11, 0.69; 95% CI 0.05, 0.53). As to skill mix, a 1 to 1 proportion of nurses to ULNs on duty marginally significantly increased the risk of fall compared to having one nurse to three ULNs (0.33). However, other risk fac- tors did not substantially affect inpatient falls, as shown in Table 3.

Multivariate analysis of risk factors for inpatient falls A multivariate conditional logistic regression model was adjusted for multiple variables associated with

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inpatient falls p ≤ 0.15, as shown in Table  3. After adjusting for the effect of proportion of skill mix, the final multivariate model showed that inpatients with acute psychosis have a 4.34 times increased risk of falling versus those with no acute psychosis condi- tion (95% CI 1.15, 18.66). Drug use ≥ 5 types of medi- cines increased the risk of falling 3.06 times versus those who used < 5 medications (95% CI 1.59, 5.88) and those taking atypical psychiatric drugs had a 2.74 times increased risk of falling versus those who did not take any atypical psychiatric drug (95% CI 1.35, 5.58). In contrast, 26–50 patients in a ward reduced the risk of falling by 0.17 compared to smaller wards of ≤ 25 patients (95% CI 0.03, 0.87), as shown in Table  4. The interaction effects among the covariates in the final model were not found. The model was appropriately fit- ted (AIC = 139.8239, BIC = 167.6691, Hosmer–Leme- show statistics = 1.05, p = 0.292).

Discussion Psychiatric inpatient falls were associated with multi- ple risk factors. Our findings differed from some past evidence and highlight the challenges for improving inpatient service. The results reveal that patient-related factors such as clinical characteristics and medication use, combined with some staffing factors, affect the risk of falling during psychiatric hospitalization.

The frequency of falls increased for each year of the study period. This increase in falls may be explained because this period coincided with improving the hospi- tal system of risk management recording. Fall incidents commonly occur mid-week during the night shift, and there may be more staff per patient on Monday than on other days or at night. Also, there are many therapeutic and administrative activities with an increased patient flow during the week’s first day. Before falling, the most common activities were those in the bathroom, followed

Table 1 Demographic data of patients who did (n = 80) and did not fall (n = 160)

*p-value calculated using paired t-test † p-value calculated using McNemar’s Chi-Square test

np refers to non significant at p-value ≤ 0.05

Variable Total Inpatient falls Controls P-value N (%) N (%)

Age, mean (S.D.), y 240 47.37 (12.95) 47.01 (13.19) np*

Min–Max = 20–70 Min–Max = 18–70 Gender

Male 162 54 (67.5) 108 (67.5) np†

Female 78 26 (32.5) 52 (32.5)

Marital status

Single, separate, divorce 168 61 (76.25) 107 (66.88) < 0.001†

Couple 72 19 (23.75) 53 (33.13)

Education level

≤ primary education 100 32 (40.00) 68 (42.50) 0.08† ≥ Secondary education 140 48 (60.00) 92 (57.50)

Fallen in past 6 months

Yes 9 9 (11.2) 0 (0.0) N/A

No 231 71 (88.8) 160 (100.0)

Diagnosis, N (%) Major diagnosis based on ICD‑10

1. Schizophrenia 140 42 (52.5) 98 (61.2) N/A

2. Bipolar disorders 25 8 (10.0) 17 (10.6)

3. Depressive disorder 12 4 (5.0) 8 (5.0)

4. Substance abuse 13 3 (3.8) 10 (6.2)

5. Alcohol dependence 16 3 (3.8) 13 (8.1)

6. Dementia or Alzheimer’s disease 3 2 (2.5) 1 (0.6)

7. Psychosis due to medical condition 12 8 (10.0) 4 (2.5)

8. Mental retardation with psychosis 11 8 (10.0) 3 (1.9)

9. Acute psychosis 3 (1.2) 2 (2.5) 1 (0.6)

10. Schizophrenia with other psychiatric disorders 5 (2.1) 0 (0.0) 5 (3.1)

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by getting up from bed/chair/wheelchair in the bedroom. The most frequent activities before falls were different in a report of inpatient fall with injury in the psychi- atric unit among veterans. The most frequent activity related to veterans’ falls was getting up from a bed, chair or wheelchair (21.3%), with bathroom-related falls at 9% [24]. These falls might be because bathroom floors in general in Southeastern Asia, including Thailand, get wet when people shower or leave something on the floor. Therefore, an analysis of the cause of falls in different cul- tures is essential for improving fall prevention.

Of clinical characteristics of psychiatric inpatients, mental illness with acute psychosis was most associated with increased risk of fall, followed by a co-occurring physical condition. The findings aligned with the pro- spective matched case–control study that reported that patients with more severe positive psychiatric symptoms were significantly associated with increased risks for fall and fall-related injury [12, 25, 26]. Also, a lack of medical problem history significantly decreased the risks for fall- related injury [12]. Simultaneously, patients taking poly- pharmacy or using five or more types of medications had a greater chance of falling. These results are consistent with a study by Cooper and colleagues [27] that polyp- harmacy, especially concurrent use of two or more psy- chotropic and psychoactive, may increase the risk of falls in a skilled nursing facility in proportion to the total use of these agents.

Among the types of medication used, this current study found that atypical antipsychotic and cardiovascular agents significantly and independently increase the risk of falls by 2.64 and 2.17 times respectively compared to those who don’t use them. Also, the use of typical antip- sychotics reduces the risk of falls 0.53 times compared to those not using them. The other psychotropic drugs were not significantly and independently associated with increased inpatient falls. This finding partly supported two previous studies in psychiatric inpatients [3, 8], which showed that atypical antipsychotics and cardiovas- cular agents affected inpatient falls. In another previous study, Lavse et  al. found that any psychotropic medica- tion including atypical antipsychotics, typical antipsy- chotics, benzodiazepines, selective serotonin reuptake inhibitors (SSRIs), atypical antidepressants, anticonvul- sants and mood stabilizers, lithium, and drugs for Alz- heimer’s disease were independently associated with the risk of falls. Also, cardiovascular agents such as ACE inhibitors, beta-blockers, calcium channel blockers, and alpha-blockers were independently related to the risk of falls [3]. Atypical antipsychotic use was associated with adverse hyperglycemic events, with the co-administra- tion of multiple antipsychotic medicines related to more adverse hyperglycemic events [28]. There was evidence

Table 2 Characteristics of incidents of falls

Level E = resulted in temporary harm to the patient and required intervention Level F = resulted in temporary harm to the patient and required initial or prolonged hospitalization

Level G = resulted in permanent patient harm

Descriptions Number of falls %

Year of falls (A.D.)

2010 8 3.3

2011 52 21.7

2012 60 25.0

2013 54 22.5

2014 66 27.8

Day of week

Monday 9 11.3

Tuesday 22 27.5

Wednesday 11 13.8

Thursday 14 17.5

Friday 8 10.0

Saturday 8 10.0

Sunday 8 10.0

Time periods of fall incidents

Daytime (7.00 a.m.–8.00 p.m.) 33 41.3

Nighttime (8.00 p.m.–7.00 a.m.) 47 58.8

Shift work

Morning shift (8.00 a.m.–16.00 p.m.) 18 22.5

Afternoon shift (16.00 p.m.–24.00 p.m.) 16 20.0

Night shift (24.00 p.m.–8.00 a.m.) 46 57.5

Unit type

Ordinary ward 53 66.3

Special or extraordinary ward 26 32.5

Pre‑ICU 1 1.3

Number of days from admission to fall

Within 7 days after admission 25 30.1

Between 8 and 14 days after admission 12 14.5

≥ 14 days after admission 46 55.4 Activity during falls

1. Slipping/falling in bathroom 34 42.5

2. Getting up from bed/chair/wheelchair 24 30.0

3. Walking 16 20.0

4. Running/climbing up 4 5.1

5. Falling down from bed 2 2.5

Location of falls

1. Bathrooms 35 43.8

2. Bedrooms 30 37.5

3. Walking/outdoor areas 10 12.6

4. Relaxation/dining room 5 6.3

Consciousness before fall

Alert 66 82.5

Confused 14 17.5

Impact of fall injury

Level E 69 86.3

Level F 10 12.5

Level G 1 1.3

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Table 3 Univariate and multivariate conditional (fixed‑effects) logistic regression of risk factors associated with inpatient falls in a matched case–control study

Variables Inpatient falls N (%)

Controls N (%)

uOR (95% CI) P-value aOR (95% CI) P-value

Clinical characteristics

Psychiatric condition

No acute psychosis 60 (75.00) 151 (94.38) 1

Having acute psychosis 20 (25.00) 9 (5.63) 6.8 (2.56–18.53) < .001 4.62 (1.14–18.66) .031*

Number of psychiatric disorders

1 70 (87.50) 150 (93.75) 1

2 10 (12.50) 10 (6.25) 2.9 (.84–5.18) .112 .75 (.16–3.56) .719

Co‑occurring physical illnesses

0 49 (61.25) 131 (81.88) 1

1–3 31 (38.75) 29 (18.13) 2.97 (1.57–5.63) < .001 1.29 (.47–3.52) .617

Number of drugs used

1–4 32 (40.00) 113 (70.63) 1

≥ 5 48 (60.00) 47 (29.38) 3.91 (2.10–7.29) < .001 2.62 (1.04–6.61) .040* Medication

Typical psychiatric drugs

No 47 (58.75) 69 (43.13) 1

Yes 33 (41.25) 91 (56.88) .53 (.31–0.92) .025 .88 (.30–2.62) .827

Atypical psychiatric drugs

No 30 (37.50) 97 (60.63) 1

Yes 50 (62.50) 63 (39.38) 2.64 (1.48–4.70) < .001 2.63 (.95–7.32) .064

Antidepressants

No 64 (80.00) 131 (81.88) 1

Yes 16 (20.00) 29 (18.13) 1.14 (.56–2.35) .712 NI

Benzodiazepines

No 14 (17.50) 39 (24.38) 1

Yes 66 (82.50) 121 (75.63) 1.52 (.77–2.99) .229 NI

Anticonvulsants

No 49 (61.25) 113 (70.63) 1

Yes 31 (38.75) 47 (29.38) 1.59 (.87–2.90) .127 .70 (.29–1.69) .424

Lithiums

No 77 (96.25) 153 (95.63) 1

Yes 3 (3.75) 7 (4.38) 0.84 (.20–3.49) .812 NI

Antiparkinsons

No 13 (16.46) 28 (17.61) 1

Yes 66 (83.54) 131 (82.39) 1.12 (.49–2.56) .781 NI

Antidiabetic agents

No 72 (90.00) 151 (94.38) 1

Yes 8 (10.00) 9 (5.63) 2.06 (.69–6.15) .192 NI

Anticholesterol agents

No 73 (91.25) 153 (95.63) 1

Yes 7 (8.75) 7 (4.38) 2.13 (.71–6.43) .181 NI

Cardiovascular agents

No 60 (75.00) 137 (85.63)

Yes 20 (25.00) 23 (14.38) 2.17 (1.05–4.51) .037 1.22 (.40–3.71) .729

Staffing factors

Number of nurses in the shift

1 35 (43.75) 76 (47.50)

2–4 45 (56.25) 84 (52.50) 1.23 (0.65–2.33) .523 NI

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that seizures may be induced by non-ketonic hyperglyce- mia [29], which possibly leads to falls occurring. Regard- ing the effect of typical and atypical antipsychotics on

risk of fall, this study’s finding showed both agreement and difference with previous studies [10, 11]. A case– control study of nursing home residents reported that both typical and atypical antipsychotic associated with increased hospitalization for femur fracture [11]. A pro- spective study [10] found that fall events in geriatric inpa- tients were related to receiving a typical antipsychotic drug (OR = 2.90, 95% CI 1.34, 6.15). A low dose (1  mg/ day) of risperidone was associated with decreased falls, especially in patients who exhibited wandering behaviors. In contrast, a 2  mg/day dosage may increase the risk of falls in ambulatory persons with a low level of wandering. Therefore, psychological and behavioral problems, type of drug, dosage, and timing of antipsychotic administra- tion affect fall incidents need to be further investigated.

Regarding staffing factors, the studies of nurse staffing and adverse outcomes in psychiatric units are scarce. Also, the circumstances and the provision of care in psychiatric units are different from medical, surgical, or other departments. However, the previous studies in five separate units in a general hospital found that the association between staffing levels and fall was not linear but was cubic spline or curve-shaped and varied by unit types, especially on step-down or medical units [17]. In these units, there was an association between nurse staffing and falling: at lower staffing levels, the

ULNs: unlicensed nurse assistants; NI: not inclusion; uOR: unadjusted odds ratio; aOR: adjusted for all variables in the table p ≤ .15); CI: confidence interval *p < 0.05

Table 3 (continued)

Variables Inpatient falls N (%)

Controls N (%)

uOR (95% CI) P-value aOR (95% CI) P-value

Nurse‑to‑patient ratio

1:1–15 20 (25.00) 17 (10.63) 1

1:16–30 43 (53.75) 96 (60.00) .28 (.11–.69) .006 .45 (.12–1.68) .237

1:31–45 17 (21.25) 47 (29.38) .17 (.06–.54) .002 1.05 (.14–7.84) .962

Number of patients in the ward

≤ 25 34 (42.50) 53 (33.13) 1 26–50 22 (27.50) 59 (36.88) .39 (.16–.95) .038 .15 (.03‑.87) .034*

≥ 51 24 (30.00) 48 (30.00) .84 (.37–1.90) .687 .35 (.04–2.90) .330 No. of ULNs in the shift

2 45 (56.25) 94 (58.75) 1

3–5 35 (43.75) 66 (41.25) 1.16 (0.60–2.23) .659 NI

Proportion of skill mix

.33 1 (1.25) 5 (3.13)

.50 34 (42.50) 72 (45.00) 3.45 (.30–39.41) .318 2.27 (.11–47.87) .598

.67 24 (30.00) 61 (38.13) 2.67 (.23–30.92) .432 6.31 (.22–181.81) .283

1.00 21 (26.25) 22 (13.75) 9.10 (.73–113.92) .087 16.54 (.46–588.42) .124

Type of unit

Ordinary ward 53 (66.25) 118 (73.75) 1

Private ward & ICU 27 (33.75) 42 (26.25) 1.48 (.80–2.72) .208 NI

Table 4 Multivariate conditional logistic regression model of risk factors associated with inpatient falls in a matched case–control study in a psychiatric hospital

The model is adjusted for acute psychotic condition, number of drugs used, atypical psychiatric drugs, number of patients in the ward, and the proportion of skill mix (.33, .50, .67, 1.00)

AIC = 139.8239; BIC = 167.6691), No interaction between covariates Model fitted appropriately (Hosmer–Lemeshow statistic = 1.05; p = .292)

Variables Adjusted OR 95% CI P-value

Acute psychosis condition

No 1

Yes 4.34 1.45–13.05 .009

Number of drugs used

1–4 1

≥ 5 3.06 1.59–5.88 .009 Atypical psychiatric drugs

No 1

Yes 2.74 1.35–5.58 .005

Number of patients in the ward

≤ 25 1 26–50 .17 .04‑.72 .015

≥ 51 .38 .08–1.74 .213

Page 9 of 11Seeherunwong et al. International Journal of Mental Health Systems (2022) 16:3

fall rate increased as staffing increased, but at moder- ate and high staffing levels, the fall rate decreased as staffing increased. The finding from this study also rein- forced the previous studies that showed a non-linear relationship between nurse per patient ratio and risk of fall. A nurse per patient ratio of 1:16–30 can lower the risk of fall better than a nurse per patient ratio of 1:31– 45 or 1:1–15. Also, the higher total number of nurses in the shift was not significantly associated with the risk of falls. This finding was consistent with a report from the study of inpatient falls in a general hospital, and skilled nursing facilities that a higher number of the nursing staff was not associated with falls occurring [17, 30]. A previous study conducted in a public hos- pital inpatient psychiatric care environment found that patient falls with injuries were not significantly related to patient-to psychiatric nurse staff ratio but were negatively associated with manager leadership skill [31]. It is possible that rather than the patient-to nurse ratio being of most importance, the quality of nursing training or awareness of the risk of falls in psychiatric inpatients is essential in preventing inpatient falls. The issue needs to be explored in further study. Likewise, 3–5 ULNs in the shift were not significantly associated with falls occurring versus two ULNs in the shift. Also, nurses’ skill mix to ULNs with ratios of 0.50 and 1.00 in the shift was not associated with falls occurring versus a mix ratio of 0.33.

The number of patients staying in the ward was not linearly related to the risk of falling. The risk of falls was reduced 0.39 times with 26–50 patients versus ≤ 25 patients in wards. On the other hand, wards with ≥ 51 patients were not significantly associated with falls. Wards with an intermediate number of patients are found in ordinary wards. The standard ward layout is an open room. There are 20–30 beds in the room. Everyone can see each other’s movements and daily activities and help each other. Therefore, falls are prevented because they are detected, and assistance is given before a severe fall occurs. In addition, these findings may result because psychiatric inpatients go through various severity phases. Some are in the acute phase, early stability phase, and stability phase. The psychiatric unit’s circumstance is to provide managed daily activities and an environment like living at a patient’s home. Daily activities are scheduled to encourage the patients to improve their psychosocial functioning. The patients can ambulate around the unit, socialize and help each other. Thus, the crowding of patients in the unit may not be a risk factor for falls. Pri- vate wards for VIP patients and pre ICU wards that sepa- rate patients with violent behavior for care in a specialty unit were not significantly associated with falls versus ordinary wards.

Finally, the multivariate model revealed that the most significant and strongest predictor for increased risk of fall incidents of psychiatric inpatients was having acute symptoms of psychosis. The second predictor was poly- pharmacy, taking five or more drugs simultaneously and the third predictor was taking atypical psychiatric drugs. This three identified predictors in the model were intrin- sic factors. An organizational element, 26–50 patients in each ward, significantly protected the risk of falls. In contrast, wards with ≥ 51 patients were not significantly associated with falls versus wards with ≤ 25 persons. This finding is consistent with Blair & Grumen’s finding that the total number of geriatric psychiatric inpatients in a ward was inversely related to the number of falls [1]. With low patient numbers, the fall rate increased, while with high patient numbers, the fall rate decreased. The possible reason is that the staff "let down their guard" when they had few patients or were more relaxed and less vigilant [1].

The research findings highlight the essential intrinsic and organizational factors that need to be considered for psychiatric hospitalization fall prevention. According to intrinsic factors, the fall risk assessment tool can detect vital risk factors to preventing falls. Regarding extrin- sic factors, hospital staff can improve the structure at the organizational level. Thailand lacks a mental health workforce, and psychiatric units are significantly under- staffed compared to the suggested norms of health staff- ing required for health facilities. According to the annual report of the Department of Mental Health, Ministry of Public Health, Thailand, in 2012, there were 1.11 psychia- trists and 6.19 nurses per 100,000 of population, working in twelve mental health services in the Bangkok area [32]. While in the E.U., there were over 24 nurses per 100,000 population working in mental health [33]. Further stud- ies need to focus on the staffing-related or organizational factors affecting patient outcomes in mental health ser- vices. There is no standardized acuity tool available for planning and managing psychiatric staff in mental health units.

Limitation This study examined a psychiatric hospital in an upper- middle-income country with a shortage of psychiatric professionals and under healthcare resources. The study used only one data source from a psychiatric hospital, so the results may not be generalizable in other countries with different contexts. Staffing numbers considered in this paper did not exclude the number of staff who joined the hospital or who had meetings out of the unit or those who took the day off for vacation or sickness. Research- ers believed that the number of inpatient falls reported in this study was much lower than the actual fall incidence.

Page 10 of 11Seeherunwong et al. International Journal of Mental Health Systems (2022) 16:3

Previous studies provide reasons for underreporting fall incidences as fellows: first, the negative attitude of staff in reporting fall incidents; second, fall with noninjury is most likely to be unreported; and third, time con- straints in filling out the reports of falls [34]. Also, for unwitnessed falls, psychiatric inpatients were less likely to accurately report the fall to staff versus patients with other diagnoses because of altered mental activity [35]. Therefore, the characteristics of falls from the reported incident to the hospital’s risk management center in this study mainly included falls with an injury with no infor- mation related to any falls reported in the medical reports or patient reports. Although our research was done some time ago, it still reflects the condition in the psychiatric ward in Thailand. It provides one of the first associations among patient and staffing factors with psychiatric inpa- tient falls in Southeast Asia. Age is a critical indicator in assessing inpatient falls. Age in this study population was not discussed since subjects were age-matched, although patients in 5-year groups may have been such a wide range that some age differences were missed.

Conclusion Fall of psychiatric inpatients is a crucial problem but can be preventable. Our findings highlight the patient-related factors for the prevention of falls. Results show acute psychotic condition, polypharmacy, and taking atypical psychiatric drugs associated with increased risk of falls. Among organizational factors, wards with between 26 and 50 patients have significantly fewer falls, an essen- tial protector from falls. Furthermore, researchers need to investigate the dosage of medications such as atypi- cal and typical antipsychotics and cardiovascular agents to see if medicine levels might increase or protect from falls. Also, the timing of typical and atypical antipsy- chotic drug administration may induce the occurrence of falls. Polypharmacy as risk means a detailed evaluation of drug interactions that may cause psychiatric inpatient falls is warranted. Regarding staffing-related factors, nei- ther R.N. nor ULN ratios or skill mix proportions were significantly associated with inpatient falls. Yet, the nec- essary ratio of staff to patient and proportion of staff mix in psychiatric units is needed to protect against inpatient falls and should be investigated and verified. Administra- tors of psychiatric hospitals need to determine workforce needs for utilizing staff availability and achieving satisfac- tory health outcomes like limiting fall incidents. There- fore, future studies should evaluate an adequate staff and skill mix that balances supply and demand for efficient quality of care to prevent adverse outcomes in psychiatric inpatients. Furthermore, a prospective study is recom- mended to investigate patient and organizational factors and effects from psychiatric inpatient falls.

Abbreviations ICUs: Intensive Care Units; CVA: Cerebrovascular Accident; RN: Register Nurse; SSRIs: Selective serotonin reuptake inhibitors; ULNs: Unlicensed Nurse Assistants.

Acknowledgements The authors would like to thank the Director and the staff of the psychiatric hospital for facilitating in data collection. The authors wish to thank Associate Dr. Mathuros Tipayamongkholkul for her help in statistical analysis. The authors also wish to thank Mr. Stephen Hamann for the English language editing.

Authors’ contributions AS contributed to conception, study design, analysis and interpret of data, drafting the manuscript and study coordination. CT conducted the analysis and interpretation of data, and provided feedback on the initial analysis. WV, & PT involved in study coordination and provided feedback on the initial analy‑ sis. AS, CT, WV & PT revising it critically for important intellectual content, and final approval of the version to be published. All authors read and approved the final manuscript.

Funding Financial support was provided for this study from China Medical Board, faculty of Nursing, Mahidol University.

Availability of data and materials The datasets used and analyzed during the current study are not publicly available due to the confidential of the risk management system of the hospi‑ tal but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate Ethics approval was obtained from the Institutional Review Board Faculty of Nursing, Mahidol University (COA No. IRB‑NS 2015/282.3004) and the ethical review board committees of the psychiatric hospital. As this study obtained data from the hospital incident reports for the risk management system and patients’ medical records, consent to participate permission to obtain data was obtained from the director of the psychiatric hospital. The waived informed consent was approved by the Institutional Review Board Faculty of Nursing, Mahidol University because the psychiatric inpatients have been discharged from the hospital for more than 1 year and therefore do not have a contact address. The research conforms to the provisions of the Declaration of Helsinki, the Belmont Report, CIOMS Guidelines.

Consent for publication Not applicable.

Competing interests The authors declare that they have no competing interests.

Author details 1 Department of Mental Health and Psychiatric Nursing, Faculty of Nursing, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pat‑ thom 73170, Thailand. 2 Nursing Division, Somdet Chaopraya Institute of Psy‑ chiatry, 112, Somdet Chaopraya Rd., Khlong San, Bangkok 10600, Thailand.

Received: 20 April 2021 Accepted: 12 January 2022

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